import torch
class Model(torch.nn.Module):
    def __init__(self):
        super().__init__()

    def forward(self, x):
        return torch.asinh(x)

from torch.onnx.symbolic_registry import register_op

def asinh_symbolic(g, input, *, out=None):
    return g.op("Asinh", input)

register_op('asinh', asinh_symbolic, '', 9)

model = Model()
input = torch.rand(1, 3, 10, 10)
torch.onnx.export(model, input, 'asinh.onnx')

